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Text Generation

Text Generation is the task of generating text with the goal of appearing indistinguishable to human-written text. This task is more formally known as "natural language generation" in the literature.

Text generation can be addressed with Markov processes or deep generative models like LSTMs. Recently, some of the most advanced methods for text generation include BART, GPT and other GAN-based approaches. Text generation systems are evaluated either through human ratings or automatic evaluation metrics like METEOR, ROUGE, and BLEU.

Further readings:

( Image credit: Adversarial Ranking for Language Generation )

Papers

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Showing 4401–4450 of 5335 papers

TitleStatusHype
Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation—0
Two-Step Training and Mixed Encoding-Decoding for Implementing a Generative Chatbot with a Small Dialogue Corpus—0
CheckYourMeal!: diet management with NLG—0
Trouble on the Road: Finding Reasons for Commuter Stress from Tweets—0
Treat the system like a human student: Automatic naturalness evaluation of generated text without reference texts—0
ChatEval: A Tool for the Systematic Evaluation of Chatbots—0
Comprehension Driven Document Planning in Natural Language Generation Systems—0
Sentence Packaging in Text Generation from Semantic Graphs as a Community Detection Problem—0
A Master-Apprentice Approach to Automatic Creation of Culturally Satirical Movie Titles—0
Neural sentence generation from formal semantics—0
Statistical NLG for Generating the Content and Form of Referring Expressions—0
Towards making NLG a voice for interpretable Machine Learning—0
Exploring Lexical-Semantic Knowledge in the Generation of Novel Riddles in Portuguese—0
Toward Bayesian Synchronous Tree Substitution Grammars for Sentence Planning—0
Content Aware Source Code Change Description Generation—0
Designing and testing the messages produced by a virtual dietitian—0
Interactive health insight miner: an adaptive, semantic-based approach—0
Explainable Autonomy: A Study of Explanation Styles for Building Clear Mental Models—0
The Task Matters: Comparing Image Captioning and Task-Based Dialogical Image Description—0
Auditing Data Provenance in Text-Generation ModelsCode0
Japanese Advertising Slogan Generator using Case Frame and Word Vector—0
Applications of NLG in practical conversational AI settings—0
Evaluation methodologies in Automatic Question Generation 2013-2018—0
The E2E NLG Challenge: A Tale of Two Systems—0
Cyclegen: Cyclic consistency based product review generator from attributes—0
Data2Text Studio: Automated Text Generation from Structured Data—0
Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction—0
E2E NLG Challenge: Neural Models vs. TemplatesCode0
E2E NLG Challenge Submission: Towards Controllable Generation of Diverse Natural Language—0
Decoding Strategies for Neural Referring Expression Generation—0
Stylistically User-Specific Generation—0
End-to-end Image Captioning Exploits Distributional Similarity in Multimodal SpaceCode0
Modelling Pro-drop with the Rational Speech Acts Model—0
Template-based multilingual football reports generation using Wikidata as a knowledge base—0
Assisted Nominalization for Academic English Writing—0
Task Proposal: The TL;DR Challenge—0
Talking about other people: an endless range of possibilitiesCode0
Being data-driven is not enough: Revisiting interactive instruction giving as a challenge for NLG—0
Textual Entailment based Question Generation—0
Multi-Language Surface Realisation as REST API based NLG Microservice—0
Extracting Linguistic Resources from the Web for Concept-to-Text Generation—0
Generating Texts with Integer Linear Programming—0
Evaluating Text GANs as Language ModelsCode0
Hierarchical Text Generation using an OutlineCode0
Skip-Thought GAN: Generating Text through Adversarial Training using Skip-Thought Vectors—0
BLEU is Not Suitable for the Evaluation of Text SimplificationCode0
Important Attribute Identification in Knowledge Graph—0
Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity—0
Adversarial Text Generation Without Reinforcement Learning—0
End-to-End Content and Plan Selection for Data-to-Text GenerationCode0
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All datasetsDARTCOCO CaptionsEMNLP2017 WMTReDialCommonGenROCStoriesChinese PoemsCzech restaurant informationOpenWebTextSciQYahoo QuestionsADGEN

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1T5B BaselineBLEU48.74—Unverified
2FactT5BBLEU48.37—Unverified
3JointGT BaselineBLEU47.51—Unverified
4FactJointGTBLEU47.39—Unverified
5Control Prefixes (T5-large)METEOR0.41—Unverified
6T5METEOR0.12—Unverified
7BARTMETEOR0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1LeakGANBLEU-20.95—Unverified
2partGANBLEU-20.91—Unverified
3RankGANBLEU-20.85—Unverified
4RelGAN (100)BLEU-20.85—Unverified
5SeqGANBLEU-20.83—Unverified
#ModelMetricClaimedVerifiedStatus
1LeakGANBLEU-20.96—Unverified
2PPOGANBLEU-20.91—Unverified
3RelGANBLEU-20.88—Unverified
4SeqGANBLEU-20.86—Unverified
5RankGANBLEU-20.78—Unverified
#ModelMetricClaimedVerifiedStatus
1UniCRSDistinct-30.65—Unverified
2CRFRDistinct-30.52—Unverified
3KGSFDistinct-30.43—Unverified
4C2CRSDistinct-30.33—Unverified
5KBRDDistinct-30.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UniLMCIDEr14.92—Unverified
2BART (TextBox 2.0)CIDEr12.98—Unverified
3BARTMETEOR0.3—Unverified
4T5METEOR0.29—Unverified
#ModelMetricClaimedVerifiedStatus
1Beam search + A*esque (beam)BLEU-134.4—Unverified
2Beam search + A*esque (sample)BLEU-134.4—Unverified
3Beam search + A*esque (greedy)BLEU-134.3—Unverified
4Beam searchBLEU-133.7—Unverified
#ModelMetricClaimedVerifiedStatus
1RankGANBLEU-20.81—Unverified
2SeqGANBLEU-20.74—Unverified
3LeakGANBLEU-20.46—Unverified
#ModelMetricClaimedVerifiedStatus
1TGen++METEOR0.17—Unverified
2TGenMETEOR0.15—Unverified
3TGen+METEOR0.15—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT2-124Meval_loss3.12—Unverified
2GPT2-81M-LOOPeval_loss3.11—Unverified
3GPT2-Hermiteeval_loss2.91—Unverified
#ModelMetricClaimedVerifiedStatus
1LLaMA-65B+CFG (zero-shot)Accuracy96.6—Unverified
2LLaMA-30B+CFG (zero-shot)Accuracy96.4—Unverified
3LLaMA-13B+CFG (zero-shot)Accuracy95.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN-VAENLL332.1—Unverified
2SA-VAENLL327.5—Unverified
3Aggressive VAENLL326.7—Unverified
#ModelMetricClaimedVerifiedStatus
1BART (TextBox 2.0)BLEU-410.2—Unverified
#ModelMetricClaimedVerifiedStatus
1STWGAN-GPBLEU-30.62—Unverified
#ModelMetricClaimedVerifiedStatus
1PALMROUGE-L41.41—Unverified
#ModelMetricClaimedVerifiedStatus
1BART (TextBox 2.0)ROUGE-L64.34—Unverified
#ModelMetricClaimedVerifiedStatus
1AEM+AttentionBLEU-114.17—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4ASR65.1—Unverified
#ModelMetricClaimedVerifiedStatus
1BART (TextBox 2.0)ROUGE-L42.96—Unverified
#ModelMetricClaimedVerifiedStatus
1Graph2SeqBLEU22—Unverified
#ModelMetricClaimedVerifiedStatus
1WGANGP + DGflowJS-40.19—Unverified